柱形图¶
In [8]:
from pyecharts import options as opts
from pyecharts.charts import Bar
bar1 = (
# 图表类型
Bar()
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90])
.add_yaxis("商家B", [20, 30, 41, 15, 45, 100])
# 配置项内容
.set_global_opts(title_opts=opts.TitleOpts(title="主标题", subtitle="副标题"))
)
bar1.render_notebook()
Out[8]:
横向柱形图¶
In [25]:
from pyecharts import options as opts
from pyecharts.charts import Bar
def bar_reversal_axis(): # 返回的Bar的类实例
bar1 = (
# 图表类型
Bar()
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90])
.add_yaxis("商家B", [20, 30, 41, 15, 45, 100])
# 翻转
.reversal_axis()
# 系列配置项
.set_series_opts(label_opts=opts.LabelOpts(position='right'))
# 配置项内容
.set_global_opts(title_opts=opts.TitleOpts(title="主标题", subtitle="副标题"))
)
return bar1
In [27]:
barh = bar_reversal_axis()
barh.render_notebook()
Out[27]:
折线图¶
In [28]:
#可以用工具箱将柱形转换为折线，或者直接修改名称
from pyecharts import options as opts
from pyecharts.charts import Line
x = ['2018-{:0>2d}'.format(s) for s in range(1,13)]
y1 = [5,10,26,30,35,30,20,26,40,46,40,50]
y2 = [8,20,24,36,40,36,40,45,50,53,48,58]
bar1 = (
# 图表类型
Line()
.add_xaxis(x)
.add_yaxis("基金A", y1)
.add_yaxis("基金B", y2)
# 配置项内容
.set_global_opts(title_opts=opts.TitleOpts(title="主标题", subtitle="副标题"))
)
bar1.render_notebook()
Out[28]:
散点图¶
In [29]:
from pyecharts.charts import Scatter
import numpy as np
import pandas as pd
df = pd.DataFrame()
df['weight'] = np.array([56,67,65,70,57,60,80,85,76,64],dtype='int32') #数组对象，必须是整型
df['height'] = np.array([162,170,168,172,168,172,180,176,178,170],dtype='int32')
df['height_m'] = [150,160,164,170,160,158,169,173,171,179]
scatter = Scatter()
scatter.add_xaxis(df['weight']) #散点图才可以是Series对象，其他的不行只能列表，Series需要进行转化
scatter.add_yaxis('男生',df['height'])
scatter.add_yaxis('女生',df['height_m'])
scatter.set_global_opts(title_opts=opts.TitleOpts(title="Scatter-基本示例"))
scatter.render_notebook()
Out[29]:
散点图数据支持series类型
箱线图¶
In [30]:
from pyecharts import options as opts
from pyecharts.charts import Boxplot
v1 = [
[850, 740, 900, 1070, 930, 850, 950, 980, 980, 880]
+ [1000, 980, 930, 650, 760, 810, 1000, 1000, 960, 960],
[960, 940, 960, 940, 880, 800, 850, 880, 900]
+ [840, 830, 790, 810, 880, 880, 830, 800, 790, 760, 800],
]
v2 = [
[890, 810, 810, 820, 800, 770, 760, 740, 750, 760]
+ [910, 920, 890, 860, 880, 720, 840, 850, 850, 780],
[890, 840, 780, 810, 760, 810, 790, 810, 820, 850, 870]
+ [870, 810, 740, 810, 940, 950, 800, 810, 870],
]
c = Boxplot() #箱线图的名称
c.add_xaxis(["expr1", "expr2"])
c.add_yaxis("A", c.prepare_data(v1)) #实线是中位数 必须加入list.prepare_data，因为他不是dataframe对象
c.add_yaxis(
"B", c.prepare_data(v2) # 计算 中位数 最小值 最大值...
)
c.set_global_opts(title_opts=opts.TitleOpts(title="BoxPlot-基本示例"))
c.render_notebook()
#数据格式最好要和上面一样
Out[30]:
饼图¶
In [41]:
from pyecharts import options as opts
from pyecharts.charts import Pie
from pyecharts.faker import Faker
c = (
Pie()
.add("", [list(z) for z in zip(Faker.choose(), Faker.values())],radius=["30%", "70%"],) #数据格式需要对等
.set_global_opts(title_opts=opts.TitleOpts(title="Pie-基本示例"))
.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {d}%")) #显示百分比
)
c.render_notebook()
Out[41]:
In [35]:
for i in zip(['a','b','c'],[1,2,3]):
print(i) #两数列对应组合
词云图¶
- jieba中文分词
- WordCloud词云库
In [42]:
from pyecharts.charts import WordCloud
words = ['python','jupyter','numpy','pandas','matplotlib','sklearn',
'xgboost','lightGBM','simpy','keras','tensorflow',
'hive','hadoop','spark']
counts = [100,90,65,95,50,60,70,70,20,70,80,80,60,60]
cloud = WordCloud()
cloud.add("文章",zip(words,counts))
cloud.render_notebook()
Out[42]:
jieba库¶
In [43]:
import jieba
In [47]:
text = '7月17日以来，河南省遭遇极端强降雨，中西部、西北部地区出现成片大暴雨，部分地区特大暴雨。根据《国家防汛抗旱应急预案》有关规定，国家防总决定于7月20日20时启动防汛Ⅲ级应急响应。 河南因为暴雨路面出现大规模积水，多名人员被困，全国各地的人民都在关心河南暴雨情况，希望他们平安度过这关。为帮助河南因强降雨受困群众，九派新闻记者陆续搜集河南各地求助信息并进行电话求证核实，并将核实到的信息滚动发布于此条评论区。如您或者家人受困需发布求助信息，可直接在此条置顶内容评论区留言，或直接联系微信号XXXX。请有力量施予援手的你，积极转发扩散'
text_list = jieba.lcut(text) #分词
arr = np.array(text_list)
arr
Out[47]:
In [53]:
np.unique(arr,return_counts=True) #统计计算词语
Out[53]:
地图¶
Map¶
In [58]:
[list(z) for z in zip(Faker.provinces, Faker.values())]
Out[58]:
In [59]:
from pyecharts import options as opts
from pyecharts.charts import Map
from pyecharts.faker import Faker
c = (
Map()
.add("商家A",[list(z) for z in zip(Faker.provinces, Faker.values())], "china") # [['北京',29],['上海',42]] #名称，数据，类型
.set_global_opts(title_opts=opts.TitleOpts(title="Map-基本示例"))
#地区重复结果就会直接相加
#世界地图需要英文，中国的就使用中文
)
c.render_notebook()
Out[59]:
Geo¶
In [60]:
from pyecharts import options as opts
from pyecharts.charts import Geo
from pyecharts.faker import Faker
#默认不显示标签，是地理地图
c = (
Geo()
.add_schema(maptype="china")
.add("geo", [list(z) for z in zip(Faker.provinces, Faker.values())])
.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
.set_global_opts(
visualmap_opts=opts.VisualMapOpts(), title_opts=opts.TitleOpts(title="Geo-基本示例")
)
)
c.render_notebook()
Out[60]:
In [62]:
import math
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Line3D
data = []
for t in range(0, 25000):
_t = t / 1000
x = (1 + 0.25 * math.cos(75 * _t)) * math.cos(_t)
y = (1 + 0.25 * math.cos(75 * _t)) * math.sin(_t)
z = _t + 2.0 * math.sin(75 * _t)
data.append([x, y, z])
c = (
Line3D()
.add(
"",
data,
xaxis3d_opts=opts.Axis3DOpts(Faker.clock, type_="value"),
yaxis3d_opts=opts.Axis3DOpts(Faker.week_en, type_="value"),
grid3d_opts=opts.Grid3DOpts(width=100, height=100, depth=100),
)
.set_global_opts(
visualmap_opts=opts.VisualMapOpts(
max_=30, min_=0, range_color=Faker.visual_color
),
title_opts=opts.TitleOpts(title="Line3D-基本示例"),
)
)
c.render_notebook()
Out[62]:
In [63]:
import pyecharts.options as opts
from pyecharts.charts import Bar3D
"""
Gallery 使用 pyecharts 1.1.0
参考地址: https://echarts.baidu.com/examples/editor.html?c=bar3d-punch-card&gl=1
目前无法实现的功能:
1、光照和阴影暂时无法设置
"""
hours = [
"12a",
"1a",
"2a",
"3a",
"4a",
"5a",
"6a",
"7a",
"8a",
"9a",
"10a",
"11a",
"12p",
"1p",
"2p",
"3p",
"4p",
"5p",
"6p",
"7p",
"8p",
"9p",
"10p",
"11p",
]
days = ["Saturday", "Friday", "Thursday", "Wednesday", "Tuesday", "Monday", "Sunday"]
data = [
[0, 0, 5],
[0, 1, 1],
[0, 2, 0],
[0, 3, 0],
[0, 4, 0],
[0, 5, 0],
[0, 6, 0],
[0, 7, 0],
[0, 8, 0],
[0, 9, 0],
[0, 10, 0],
[0, 11, 2],
[0, 12, 4],
[0, 13, 1],
[0, 14, 1],
[0, 15, 3],
[0, 16, 4],
[0, 17, 6],
[0, 18, 4],
[0, 19, 4],
[0, 20, 3],
[0, 21, 3],
[0, 22, 2],
[0, 23, 5],
[1, 0, 7],
[1, 1, 0],
[1, 2, 0],
[1, 3, 0],
[1, 4, 0],
[1, 5, 0],
[1, 6, 0],
[1, 7, 0],
[1, 8, 0],
[1, 9, 0],
[1, 10, 5],
[1, 11, 2],
[1, 12, 2],
[1, 13, 6],
[1, 14, 9],
[1, 15, 11],
[1, 16, 6],
[1, 17, 7],
[1, 18, 8],
[1, 19, 12],
[1, 20, 5],
[1, 21, 5],
[1, 22, 7],
[1, 23, 2],
[2, 0, 1],
[2, 1, 1],
[2, 2, 0],
[2, 3, 0],
[2, 4, 0],
[2, 5, 0],
[2, 6, 0],
[2, 7, 0],
[2, 8, 0],
[2, 9, 0],
[2, 10, 3],
[2, 11, 2],
[2, 12, 1],
[2, 13, 9],
[2, 14, 8],
[2, 15, 10],
[2, 16, 6],
[2, 17, 5],
[2, 18, 5],
[2, 19, 5],
[2, 20, 7],
[2, 21, 4],
[2, 22, 2],
[2, 23, 4],
[3, 0, 7],
[3, 1, 3],
[3, 2, 0],
[3, 3, 0],
[3, 4, 0],
[3, 5, 0],
[3, 6, 0],
[3, 7, 0],
[3, 8, 1],
[3, 9, 0],
[3, 10, 5],
[3, 11, 4],
[3, 12, 7],
[3, 13, 14],
[3, 14, 13],
[3, 15, 12],
[3, 16, 9],
[3, 17, 5],
[3, 18, 5],
[3, 19, 10],
[3, 20, 6],
[3, 21, 4],
[3, 22, 4],
[3, 23, 1],
[4, 0, 1],
[4, 1, 3],
[4, 2, 0],
[4, 3, 0],
[4, 4, 0],
[4, 5, 1],
[4, 6, 0],
[4, 7, 0],
[4, 8, 0],
[4, 9, 2],
[4, 10, 4],
[4, 11, 4],
[4, 12, 2],
[4, 13, 4],
[4, 14, 4],
[4, 15, 14],
[4, 16, 12],
[4, 17, 1],
[4, 18, 8],
[4, 19, 5],
[4, 20, 3],
[4, 21, 7],
[4, 22, 3],
[4, 23, 0],
[5, 0, 2],
[5, 1, 1],
[5, 2, 0],
[5, 3, 3],
[5, 4, 0],
[5, 5, 0],
[5, 6, 0],
[5, 7, 0],
[5, 8, 2],
[5, 9, 0],
[5, 10, 4],
[5, 11, 1],
[5, 12, 5],
[5, 13, 10],
[5, 14, 5],
[5, 15, 7],
[5, 16, 11],
[5, 17, 6],
[5, 18, 0],
[5, 19, 5],
[5, 20, 3],
[5, 21, 4],
[5, 22, 2],
[5, 23, 0],
[6, 0, 1],
[6, 1, 0],
[6, 2, 0],
[6, 3, 0],
[6, 4, 0],
[6, 5, 0],
[6, 6, 0],
[6, 7, 0],
[6, 8, 0],
[6, 9, 0],
[6, 10, 1],
[6, 11, 0],
[6, 12, 2],
[6, 13, 1],
[6, 14, 3],
[6, 15, 4],
[6, 16, 0],
[6, 17, 0],
[6, 18, 0],
[6, 19, 0],
[6, 20, 1],
[6, 21, 2],
[6, 22, 2],
[6, 23, 6],
]
data = [[d[1], d[0], d[2]] for d in data]
(
Bar3D(init_opts=opts.InitOpts(width="1600px", height="800px"))
.add(
series_name="",
data=data,
xaxis3d_opts=opts.Axis3DOpts(type_="category", data=hours),
yaxis3d_opts=opts.Axis3DOpts(type_="category", data=days),
zaxis3d_opts=opts.Axis3DOpts(type_="value"),
)
.set_global_opts(
visualmap_opts=opts.VisualMapOpts(
max_=20,
range_color=[
"#313695",
"#4575b4",
"#74add1",
"#abd9e9",
"#e0f3f8",
"#ffffbf",
"#fee090",
"#fdae61",
"#f46d43",
"#d73027",
"#a50026",
],
)
)
.render_notebook()
)
Out[63]:
布局¶
In [64]:
from pyecharts import options as opts
from pyecharts.charts import Bar, Line
from pyecharts.faker import Faker
v1 = [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3]
v2 = [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3]
v3 = [2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 23.4, 23.0, 16.5, 12.0, 6.2]
bar = (
Bar()
.add_xaxis(Faker.months)
.add_yaxis("蒸发量", v1)
.add_yaxis("降水量", v2)
.extend_axis(
yaxis=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(formatter="{value} °C"), interval=5
)
)
.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
.set_global_opts(
title_opts=opts.TitleOpts(title="Overlap-bar+line"),
yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(formatter="{value} ml")),
)
)
line = Line().add_xaxis(Faker.months).add_yaxis("平均温度", v3, yaxis_index=1)
bar.overlap(line)
bar.render_notebook()
Out[64]:
并行多图Grid¶
In [73]:
from pyecharts import options as opts
from pyecharts.charts import Bar, Geo, Grid
from pyecharts.faker import Faker
bar = (
Bar()
.add_xaxis(Faker.choose())
.add_yaxis("商家A", Faker.values())
.add_yaxis("商家B", Faker.values())
.set_global_opts(legend_opts=opts.LegendOpts(pos_left="20%"))
)
geo = (
Geo()
.add_schema(maptype="china")
.add("geo", [list(z) for z in zip(Faker.provinces, Faker.values())])
.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
.set_global_opts(
visualmap_opts=opts.VisualMapOpts(),
title_opts=opts.TitleOpts(title="Grid-Geo-Bar"),
)
)
grid = (
Grid(init_opts=opts.InitOpts(width="900px",height="900px")) #加大画布大小也行
.add(bar,grid_opts=opts.GridOpts(pos_left="10%",pos_top="80%",is_show=True)) #调整间距，来避免重合
.add(geo,grid_opts=opts.GridOpts(pos_left="90%",pos_top="10%",is_show=True)) #调整间距，来避免重合
# .add(bar,grid_opts=opts.GridOpts(pos_left="10%",pos_top="80%"))
)
In [74]:
grid.render_notebook()
Out[74]:
顺序多图¶
In [75]:
from pyecharts import options as opts
from pyecharts.charts import Bar, Geo, Page
from pyecharts.faker import Faker
bar = (
Bar()
.add_xaxis(Faker.choose())
.add_yaxis("商家A", Faker.values())
.add_yaxis("商家B", Faker.values())
.set_global_opts(legend_opts=opts.LegendOpts(pos_left="20%"))
)
geo = (
Geo()
.add_schema(maptype="china")
.add("geo", [list(z) for z in zip(Faker.provinces, Faker.values())])
.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
.set_global_opts(
visualmap_opts=opts.VisualMapOpts(),
title_opts=opts.TitleOpts(title="Grid-Geo-Bar"),
)
)
page = (
Page()
.add(bar) #没有参数，不能设置
.add(geo) #没有参数，不能设置
)
In [76]:
page.render_notebook()
Out[76]:
选项卡¶
In [77]:
from pyecharts import options as opts
from pyecharts.charts import Bar, Geo, Tab
from pyecharts.faker import Faker
bar = (
Bar()
.add_xaxis(Faker.choose())
.add_yaxis("商家A", Faker.values())
.add_yaxis("商家B", Faker.values())
.set_global_opts(legend_opts=opts.LegendOpts(pos_left="20%"))
)
geo = (
Geo()
.add_schema(maptype="china")
.add("geo", [list(z) for z in zip(Faker.provinces, Faker.values())])
.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
.set_global_opts(
visualmap_opts=opts.VisualMapOpts(),
title_opts=opts.TitleOpts(title="Grid-Geo-Bar"),
)
)
tab = (
Tab()
.add(geo,"地图")
.add(bar,"柱形图")
)
In [78]:
tab.render_notebook() #组件选项卡
Out[78]:
时间线轮播¶
In [79]:
from pyecharts import options as opts
from pyecharts.charts import Pie, Timeline
from pyecharts.faker import Faker
attr = Faker.choose()
t1 = Timeline()
for i in range(2015,2021):
pie = (
Pie()
.add(
"商家A",
[list(z) for z in zip(attr,Faker.values())],
# rosetype="area",
# radius=["30%","55%"],
)
.set_global_opts(title_opts=opts.TitleOpts('某商店{}年营业额'.format(i)))
)
t1.add(pie,"{}年".format(i))
t1.render_notebook() #下面有时间线
Out[79]:
在ppt中插入Pyecharts图表 https://www.cnblogs.com/mark-wq/p/14168535.html
html要改ie内核： 加上：< meta http-equiv="X-UA-Compatible" content="IE=EmulateIE10"/>
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